CTOs are navigating an AI ecosystem filled with diverse applications, from developer productivity to business operations, but face significant information asymmetry. This guide aims to equip them with foundational knowledge to make confident AI strategy decisions. AI, encompassing technologies that mimic human intelligence, is beneficial for businesses handling unstructured data or requiring automation of complex tasks. Machine learning (ML) and its subset, deep learning (DL), offer powerful pattern recognition and decision-making capabilities through neural networks and multi-layered architectures, with applications in recommendation engines and natural language processing. Reinforcement learning (RL) allows agents to optimize decision-making through interaction with their environment. However, investing in AI should be aligned with a company's technical maturity and strategic goals, as AI's probabilistic nature introduces challenges in creating reliable, production-grade systems. Successful AI adoption requires evolving development practices, integrating cross-functional teams, and leveraging strategic frameworks like the Tech Radar to identify and pursue AI opportunities aligned with business objectives.